There is abundant evidence that local signals from tissue-specific extracellular matrix microenvironments significantly affect cellular differentiation, phenotypic expression and maintenance. Substrate biophysical signals, such as soluble factors, cell-ligand interactions, matrix elasticity and geometry play a critical role in a diversity of biological events including cell adhesion, growth, differentiation, and apoptosis. Together, these signals converge to provide a multifaceted, complex mechano-chemical signaling environment for highly-specific tissue morphogenesis and regeneration. Despite accumulated knowledge regarding individual and combined roles of various mechano-chemical ECM signals in stem cell activities, the intricacy exhibited by cellular microenvironments poses a considerable challenge in resolving the mechanisms ascribed to stem cell behavior and fate processes. This complexity mandates a systemic approach whereby integrative studies must be expanded to capture a more comprehensive understanding of the determinants which direct stem cell differentiation toward desired cell type and function. Conventional methods to elucidate these mechanisms have traditionally been executed in large scale, two-dimensional tissue culture platforms which are often limited by combinatorial brevity, substrate production, and reagent supply. Furthermore, these signals, matrix and biophysical microenvironment, are often observed independently to differentiate cells on 2D substrates, an environment vastly different from the way cells are presented naturally in vivo, i.e. in 3D tissue, which elicits multiple signal inputs to regulate cell fate.
High through-put approaches have emerged in recent years to circumvent the limitations of traditional low-through-put techniques (i.e. conventional cultureware), with the promise of developing complex platforms for combined biomolecule/substrate discovery. The salient features of microarray technology include the reproducibility and screening of multiple microenvironments with significantly less reagent and substrate requirements than traditional methods, while lending improved deconstruction of complex multivariable studies. Several reports have demonstrated ECM protein microarrays, soluble factor screening, biomaterial chemistry screening, and multiple signal integration arrays (i.e. elasticity and chemical factor) with encouraging results. However, despite the versatility afforded by current microarray technologies, the incorporation of multiple signals within engineered microarrays remain limited, and combinatorial microarray technologies in three-dimensions, coupled with other biophysical properties, such as tunable stiffness and geometry, have not been demonstrated. Capturing complex, multifaceted 3-dimensional environments in high-throughput with combinatorial signaling will likely prove a necessity in designing and using tissue regeneration biomaterial platforms.